{"id":"W3180159491","doi":"10.32920/ryerson.14649096.v1","title":"Statistics Based Neural Networks Method for Industrial Image Inspection","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Industrial Vision Systems and Defect Detection","field":"Engineering","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Toronto Metropolitan University","funders":"","keywords":"Artificial neural network; Artificial intelligence; Computer science; Image (mathematics); Pixel; Computer vision; Pattern recognition (psychology); Set (abstract data type); Image processing","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.0005832171,0.000341678,0.0005213633,0.0001754711,0.0001096841,0.0003574172,0.0001179579,0.001094699,0.0001366199],"category_scores_gemma":[0.0001827532,0.0003487964,0.0002344826,0.000198112,0.00001306906,0.00007832149,0.00007940483,0.001147284,0.000003292903],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.000223998,"about_ca_system_score_gemma":0.0000867402,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0003124514,"about_ca_topic_score_gemma":0.00008784667,"domain_scores_codex":[0.9983342,0.0001548848,0.0005858626,0.000404823,0.0002130047,0.0003071883],"domain_scores_gemma":[0.9988481,0.0003269951,0.0001257199,0.0003735177,0.0002265658,0.00009913353],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.00005632908,0.00001507421,0.00001153885,0.0001359395,0.00008598874,0.000007437533,0.00002315736,0.9254836,0.000458789,0.00006277308,0.03212307,0.04153625],"study_design_scores_gemma":[0.0009476601,0.00006578097,0.00001898073,0.00006863398,0.00007566496,0.000005111667,0.00006427113,0.9927485,0.002619371,0.00004904592,0.002979056,0.0003579144],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.001830337,0.00006578286,0.9811602,0.0000197947,0.01410238,0.0009854723,0.0001952666,0.0008878351,0.0007529692],"genre_scores_gemma":[0.696804,0.00001809251,0.2907581,0.000106057,0.009663811,0.0006159961,0.001428868,0.0002667848,0.0003382852],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6949736,"threshold_uncertainty_score":0.9998964,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04581650831560533,"score_gpt":0.2957206449281434,"score_spread":0.2499041366125381,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}